The fingerprint recognition technology has been widely used in variety of fields, including crime investigation, physical and logical access control, time and attendance. The basic task of fingerprint recognition is to determine if two given fingerprints are from the same finger or not. Because different fingerprint images are usually captured in different poses (even if they are from the same finger), the two fingerprints to be compared have to be registered into the same pose. There are two types of methods for unifying the poses of two fingerprints to be compared: pairwise registration and absolute registration. Pairwise registration means that the registration is obtained based on the two given fingerprints. If a given fingerprint has to be compared with N (N can be more than millions in police fingerprint recognition systems) fingerprints in the database, the pairwise registration has to be performed N times and thus it is very inefficient. For absolute registration, only one registration is required for each fingerprint and thus it is very efficient especially for searching a given fingerprint in a large fingerprint database. Here, we consider only absolute registration.
In the related art, the fingerprint is registered according to local characteristics such as a consistency of a gray gradient and a gray variance. The methods in the related art have a good performance when the background of the fingerprint image is clean. However, these methods hardly register the fingerprint when the background of the fingerprint image is complicated. Specifically, when the background of the fingerprint image is complicated, the methods in the related art only can judge whether a local region of the fingerprint image is a fingerprint region (i.e., the region containing the fingerprint), but cannot estimate the central point and the direction of the fingerprint image. Thus, the methods in the related art cannot register the fingerprint image when the central region of the fingerprint is missing.
In order to solve the above problems, the fingerprint region should be manually cut out from the fingerprint image by the fingerprint expert, and the fingerprint should be manually registered to a unified pose (the center of the fingerprint is located in the center of the fingerprint image and the direction of fingerprint is the vertical direction) by the fingerprint expert. Alternatively, a pose estimation algorithm may be combined with the fingerprint matching algorithm to registered fingerprint. However, the process of manually registering the fingerprint by the fingerprint expert is complicated and consumes much time and effort, and the method of registering the fingerprint with the fingerprint matching algorithm is complicated, has a heavy computation, a low matching efficiency and a low matching accuracy.